Cancer reports (Hoboken, N.J.) · 2026
Molecular Characteristics, Potential Mechanisms, and Prognostic Gene Model of Younger Female Patients With Gastric Cancer.
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Luan Xiaoyi, Zhao Lulu, Wang Wanqing, Niu Penghui, Han Xue, Wang Zerong, Zhang Xiaojie, Zhao Dongbing, Chen Yingtai
Аннотация
BACKGROUND: Male patients were twice as likely to develop gastric cancer (GC) compared to females, partly due to the protective effect of estrogen. However, the proportion of females increased in the young GC patients.
AIMS: The study was designed to explore comprehensive molecular profiles of younger female GC patients, as well as develop a prognostic gene model for female GC patients.
MATERIALS&METHODS: Gene expression and clinical data of GC and nontumor patients were downloaded from the Gene Expression Omnibus (GEO) database. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were used to find molecular characteristics and potential mechanisms of younger female GC patients. The prognostic gene model containing six differential expressed genes (DEGs), which were between younger and older female patients, was established using Lasso-Cox regression. Its performance was validated by external validation. Then, receiver operating characteristic (ROC) curve was applied to determine the prognostic value of the prognostic gene model.
RESULTS: Six GEO cohorts with 305 female GC patients (69 younger patients and 236 older patients) and 38 female nontumor patients were included. A total of 4557 DEGs between female GC patients and nontumor patients were identified, including 2212 upregulated genes and 2345 downregulated genes. Estrogen response early (p < 0.001) and estrogen response late (p < 0.001) were enriched in female GC patients. In KEGG analysis, aldosterone (p = 0.023) and relaxin pathways (p = 0.043) were concentrated in the younger group. Moreover, we further used the GSE84437 cohort to construct a prognostic gene model containing six genes, namely NREP, GAD1, SLCO4A1, KRT17, DEFB1, and P3H2, to predict the overall survival (OS) of female GC patients (AUC = 0.810). In the overall analysis of female GC patients, high-risk patients showed worse OS than low-risk patients (HR = 5.7688, 95% CI: 3.0108-11.0530, p < 0.001). Compared with older female patients, younger female patients had a higher tendency to be in the high-risk group (31.1% vs. 18.3%, p = 0.018).
CONCLUSIONS: In conclusion, we provided the comprehensive molecular profiles of younger female GC patients and found that there was a significant difference in enriched hormone-related pathways between the younger group and the older group. Compared with older female patients, younger female patients were more likely to be in the high-risk group, which showed worse OS than low-risk patients.
AIMS: The study was designed to explore comprehensive molecular profiles of younger female GC patients, as well as develop a prognostic gene model for female GC patients.
MATERIALS&METHODS: Gene expression and clinical data of GC and nontumor patients were downloaded from the Gene Expression Omnibus (GEO) database. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were used to find molecular characteristics and potential mechanisms of younger female GC patients. The prognostic gene model containing six differential expressed genes (DEGs), which were between younger and older female patients, was established using Lasso-Cox regression. Its performance was validated by external validation. Then, receiver operating characteristic (ROC) curve was applied to determine the prognostic value of the prognostic gene model.
RESULTS: Six GEO cohorts with 305 female GC patients (69 younger patients and 236 older patients) and 38 female nontumor patients were included. A total of 4557 DEGs between female GC patients and nontumor patients were identified, including 2212 upregulated genes and 2345 downregulated genes. Estrogen response early (p < 0.001) and estrogen response late (p < 0.001) were enriched in female GC patients. In KEGG analysis, aldosterone (p = 0.023) and relaxin pathways (p = 0.043) were concentrated in the younger group. Moreover, we further used the GSE84437 cohort to construct a prognostic gene model containing six genes, namely NREP, GAD1, SLCO4A1, KRT17, DEFB1, and P3H2, to predict the overall survival (OS) of female GC patients (AUC = 0.810). In the overall analysis of female GC patients, high-risk patients showed worse OS than low-risk patients (HR = 5.7688, 95% CI: 3.0108-11.0530, p < 0.001). Compared with older female patients, younger female patients had a higher tendency to be in the high-risk group (31.1% vs. 18.3%, p = 0.018).
CONCLUSIONS: In conclusion, we provided the comprehensive molecular profiles of younger female GC patients and found that there was a significant difference in enriched hormone-related pathways between the younger group and the older group. Compared with older female patients, younger female patients were more likely to be in the high-risk group, which showed worse OS than low-risk patients.